Adjusting input samples in turbo equalization schemes to break trapping sets

ABSTRACT

In one embodiment, a turbo equalizer has a channel detector that receives equalized samples and generates channel soft-output values. An LDPC decoder attempts to decode the channel soft-output values to recover an LDPC-encoded codeword. If the decoder converges on a trapping set, then an adjustment block selects one or more of the equalized samples based on one or more specified conditions and adjusts the selected equalized samples. Selection may be performed by identifying the locations of unsatisfied check nodes of the last local decoder iteration and selecting the equalized samples that correspond to bit nodes of the LDPC-encoded codeword that are connected to the unsatisfied check nodes. Adjustment of the equalized samples may be performed using any combination of scaling, offsetting, and saturation. Channel detection is then performed using the adjusted equalized samples to generate an updated set of channel soft-output values, which are subsequently decoded by the decoder.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of the filing date of U.S.provisional application No. 61/089,297, filed on Aug. 15, 2008, theteachings of which are incorporated herein by reference in theirentirety.

The subject matter of this application is related to U.S. patentapplication Ser. No. 12/113,729 filed May 1, 2008, U.S. patentapplication Ser. No. 12/113,755 filed May 1, 2008, U.S. patentapplication Ser. No. 12/323,626 filed Nov. 26, 2008, U.S. patentapplication Ser. No. 12/401,116 filed Mar. 10, 2009, PCT patentapplication no. PCT/US08/86523 filed Dec. 12, 2008, PCT patentapplication no. PCT/US08/86537 filed Dec. 12, 2008, PCT patentapplication no. PCT/US09/39918 filed Apr. 8, 2009, PCT application no.PCT/US09/39279 filed on Apr. 2, 2009, U.S. patent application Ser. No.12/420,535 filed Apr. 8, 2009, U.S. patent application Ser. No.12/475,786 filed Jun. 1, 2009, U.S. patent application Ser. No.12/260,608 filed on Oct. 29, 2008, PCT patent application no.PCT/US09/41215 filed on Apr. 21, 2009, U.S. patent application Ser. No.12/427,786 filed on Apr. 22, 2009, U.S. patent application Ser. No.12/492,328 filed on Jun. 26, 2009, U.S. patent application Ser. No.12/492,346 filed on Jun. 26, 2009, U.S. patent application Ser. No.12/492,357 filed on Jun. 26, 2009, U.S. patent application Ser. No.12/492,374 filed on Jun. 26, 2009, and U.S. patent application Ser. No.12/538,915 filed on Aug. 11, 2009, the teachings of all of which areincorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to signal processing, and, in particular,to error-correction encoding and decoding techniques such as low-densityparity-check (LDPC) encoding and decoding.

2. Description of the Related Art

In attempting to recover an error-correction-encoded codeword, anerror-correction decoder may encounter one or more trapping sets thatprevent the decoder from properly decoding the codeword. Trapping sets,which represent subgraphs in a Tanner graph of an error-correction code,typically have a strong influence on error-floor characteristics of theerror-correction code because a trapping set may force the decoder toconverge to an incorrect result. To improve error-floor characteristics,a turbo equalizer, in which the error-correction decoder resides, mayemploy different techniques to, for example, (i) break the trapping setsand/or (ii) prevent the error-correction decoder from converging ontrapping sets.

SUMMARY OF THE INVENTION

In one embodiment, the present invention is an apparatus for recoveringan error-correction (EC)-encoded codeword from a set of input samples.The apparatus comprises an EC decoder, an adjuster, and a channeldetector. The EC decoder performs EC decoding to attempt to recover theEC-encoded codeword and generates a first set of soft-output values,where each soft-output value corresponding to a bit of the EC-encodedcodeword. The adjuster adjusts, if the EC decoder converges on atrapping set, one or more of the input samples to generate an adjustedset of input samples, and the apparatus determines whether one or morespecified conditions exist to select the one or more input samples foradjustment. The channel detector performs channel detection to generatea second set of soft-output values for subsequent EC decoding, whereeach soft-output value in the second set corresponds to a bit of theEC-encoded codeword. The second set of soft-output values is generatedbased on (i) the adjusted set of input samples and (ii) the first set ofsoft-output values.

In another embodiment, the present invention is a method for recoveringan error-correction (EC)-encoded codeword from a set of input samples.In particular, EC decoding is performed to attempt to recover theEC-encoded codeword, and a first set of soft-output values (e.g., Extn)is generated where, each soft-output value corresponds to a bit of theEC-encoded codeword. If the EC decoding converges on a trapping set,then a determination is made as to whether one or more specifiedconditions exist to select one or more of the input samples foradjustment. The one or more input samples selected are adjusted togenerate an adjusted set of input samples. Channel detection (e.g., DH)is then performed to generate a second set of soft-output values forsubsequent EC decoding, where each soft-output value in the second setcorresponds to a bit of the EC-encoded codeword. The second set ofsoft-output values is generated based on (i) the adjusted set of inputsamples and (ii) the first set of soft-output values.

BRIEF DESCRIPTION OF THE DRAWINGS

Other aspects, features, and advantages of the present invention willbecome more fully apparent from the following detailed description, theappended claims, and the accompanying drawings in which like referencenumerals identify similar or identical elements.

FIG. 1 shows a simplified block diagram of one implementation of aconventional hard-disk drive (HDD) system;

FIG. 2 shows a simplified block diagram of a turbo equalizer accordingto one embodiment of the present invention;

FIG. 3 a simplified flow diagram of processing performed by a turboequalizer such as the turbo equalizer of FIG. 2 according to oneembodiment of the present invention;

FIG. 4 shows a simplified block diagram of a turbo equalizer accordingto another embodiment of the present invention; and

FIG. 5 shows a simplified flow diagram of processing performed by aturbo equalizer such as the turbo equalizer of FIG. 4 according to oneembodiment of the present invention.

DETAILED DESCRIPTION

Reference herein to “one embodiment” or “an embodiment” means that aparticular feature, structure, or characteristic described in connectionwith the embodiment can be included in at least one embodiment of theinvention. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment, nor are separate or alternative embodiments necessarilymutually exclusive of other embodiments. The same applies to the term“implementation.”

FIG. 1 shows a simplified block diagram of one implementation of aconventional hard-disk drive (HDD) system 100. HDD system 100 hascontroller 102 and recording channel 104, which are used to writeincoming data to, and read outgoing data from, one or more HDD platters106. In writing mode, controller 102 receives an input data stream from,for example, a user application, and encodes the input data stream usingerror-detection encoder 108. Error-detection encoder 108 may implementan error-detection encoding scheme such as cyclic-redundancy-check (CRC)encoding or any other suitable error-detection encoding scheme. Althoughnot shown, controller 102 may also perform other suitable processing(not shown), such as run-length encoding, to prepare the input datastream for processing by recording channel 104.

Controller 102 provides the input data stream to recording channel 104,which prepares the input data stream for storage on HDD platter 106. Inso doing, recording channel 104 may implement an interleaving scheme toreduce the effects that burst errors have on recovering the input datastream after it is stored on HDD platter 106. Recording channel 104shows one exemplary interleaving scheme, in which the user data streamis interleaved to generate the error-correction-encoded codeword, butthe data written to HDD platter 106 is not interleaved (i.e.,interleaving is performed in the error-correction encoder/decoderdomain). As shown, the input data stream is provided to interleaver (π)110 and the lower input of multiplexer 116. Interleaver 110 interleavesthe input data stream and provides the interleaved input data stream toerror-correction encoder 112. Error-correction encoder 112 encodes theinterleaved input data stream using a suitable error-correction encodingtechnique such as low-density parity-check (LDPC) encoding to generatean error-correction-encoded codeword. The parity bits of theerror-correction-encoded codeword are then de-interleaved usingde-interleaver (π⁻¹) 114, and the de-interleaved parity bits areprovided to the upper input of multiplexer 116. Multiplexer 116 outputsthe input (un-interleaved) user data stream, and in so doing, insertsthe de-interleaved parity bits within the input user data stream. Theinput user data stream, with inserted de-interleaved parity bits, isthen processed using pre-processor 118, which performs processing suchas digital-to-analog conversion, pre-amplification, and possibly othersuitable processing to prepare the input user data stream and theinserted parity bits for storage on HDD platter 106.

In reading mode, recording channel 104 retrieves analog data stored onHDD platter 106 and processes the analog data using post-processor 120.Post-processor 120 performs, for example, amplification,analog-to-digital conversion, finite-impulse-response (FIR) filtering,equalization, and possibly other processing suitable for retrieving datafrom HDD platter 106. Samples y_(n) of the equalized, retrieved datastream are provided to turbo equalizer 122, which has at least onechannel detector 124 and at least one error-correction decoder 130.Turbo equalizer 122 may be implemented in many different ways, and thedetails of turbo equalizer 122 are provided merely to illustrate thebasic components of an exemplary turbo equalizer.

Channel detector 124 implements a suitable detection technique, such asViterbi soft-output detection or maximum a posteriori (MAP) detection,to generate an initial soft-output value L_(n) ⁽⁰⁾ (e.g., alog-likelihood ratio (LLR)) corresponding to each bit n of theerror-correction-encoded codeword. Note that, as used in thisspecification, the term “soft-output value” does not encompass equalizedsamples y_(n) generated by post-processor 120. Further, the term“soft-output value” refers to a value comprising a hard-decision bit(i.e., the most-significant bit) and at least one confidence value bit(i.e., the least-significant bits). Depending on the implementation,soft-output values can be implemented in, for example, sign-magnitudeformat, two's complement format, or any other suitable format. Theinitial soft-output values L_(n) ⁽⁰⁾ are interleaved by interleaver 126,which performs interleaving analogous to that of interleaver 110. Byinterleaving the initial soft-output values L_(n) ⁽⁰⁾, any burst errorsthat are present upon retrieving the input data stream stored on HDDplatter 106 may be spread out among the initial soft-output values L_(n)⁽⁰⁾. The interleaved soft-output values L_(n) ⁽⁰⁾ are provided toerror-correction decoder 130, which implements an error-correctiondecoding scheme, such as LDPC decoding, to recover the originalerror-correction-encoded codeword generated by error-correction encoder112.

During each local iteration of error-correction decoder 130,error-correction decoder 130 generates a set of updated soft-outputvalues P_(n), each value P_(n) corresponding to one bit n of theerror-correction-encoded codeword. A local iteration is an iterationthat is performed within error-correction decoder 130 itself, and doesnot involve channel detection or interleaving/de-interleaving. Upongenerating a set of updated soft-output values P_(n), a parity check isperformed using the hard-decision bits {circumflex over (x)}_(n) of theupdated soft-output values P_(n) to determine whether error-correctiondecoder 130 has converged on a valid codeword. A detailed discussion ofa parity check in the context of LDPC decoding is provided in U.S.patent application Ser. No. 12/538,915 filed on Aug. 11, 2009, theteachings all of which are incorporated herein by reference in theirentirety. The following discussion briefly summarizes these teachings.

In LDPC decoding, a parity check is performed by multiplying a vector{circumflex over (x)}, formed from the set of hard-decision bits{circumflex over (x)}_(n), by the transpose H^(T) of the LDPCparity-check matrix (i.e., H-matrix) used to generate theerror-correction-encoded codeword. The resulting product is a vector,often referred to as the syndrome, and each bit of the syndromecorresponds to one row (i.e., check node) of the LDPC parity-checkmatrix. If one or more elements of the resulting syndrome is equal toone (i.e., {circumflex over (x)}H^(T)≠0), then error-correction decoder130 has not converged on a valid codeword. Each element of the syndromethat has a value of one is considered an unsatisfied check node, andeach element of the syndrome that has a value of zero is either (i) asatisfied check node or (ii) a missatisfied check node (i.e., a checknode that falsely shows as satisfied).

If each element of the resulting syndrome is equal to zero (i.e.,{circumflex over (x)}H^(T)=0), then error-correction decoder 130 hasconverged on a valid codeword. In this case, the hard-decision bitsx_(n) are de-interleaved by de-interleaver 132, and the de-interleavedhard-decision bits x_(n) are provided to error-detection decoder 134,which may perform, for example, a cyclic-redundancy check (CRC) todetermine whether the valid codeword is the correct codeword (i.e., thecodeword that was written to HDD platter 106). When CRC is part of theencoding scheme, typically a number r of CRC bits are appended to theuser data by error-detection encoder 108 such that, upon decoding,vector {circumflex over (x)} comprises (i) the user data transmitted bythe transmitter and (ii) the r CRC bits. To perform the CRC, the userdata may be divided by a keyword that is known a priori by the receiverand the remainder of the division process may be compared to the r CRCbits. If the remainder is equal to the r CRC bits, then error-correctiondecoder 130 has converged on the correct codeword. If the remainder isnot equal to the r CRC bits, then error-correction decoder 130 hasconverged on a valid codeword that is not the correct codeword (i.e.,the valid codeword has one or more missatisfied check nodes). In thiscase, further actions may be taken to recover the correct codeword, suchas a re-read of the data.

If, after a predetermined number of local iterations, error-correctiondecoder 130 does not converge on a valid codeword, then the controllermay (i) determine the number of unsatisfied check nodes and (ii) comparethe number of unsatisfied check nodes to a specified threshold value(e.g., 16). The specified threshold value, which may be determinedexperimentally, may be used to predict whether error-correction decoder130 has (i) converged on a trapping set or (ii) experienced an error inthe communication channel that does not correspond to convergence on atrapping set. If the number of unsatisfied check nodes is greater thanor equal to the specified threshold value, then it is likely thaterror-correction decoder 130 has experienced an error in thecommunication channel. Such errors may result from, for example, a flawon HDD platter 106 or excessive noise in the communication channel. Whensuch errors occur, further action, such as re-reading of the data, maybe needed to recover the correct codeword. In some cases,error-correction decoder 130 might not be capable of recovering thecorrect codeword.

If, after the predetermined number of local iterations, the number ofunsatisfied check nodes is less than the specified threshold value, thenit is likely that error-correction decoder 130 has converged on atrapping set. A trapping set may be defined as a set of w bit nodes(i.e., columns of the LDPC parity-check matrix) that converges on asyndrome having a set of v odd-degree check nodes (i.e., unsatisfiedcheck nodes) and an arbitrary number of even-degree check nodes (i.e.,satisfied and/or missatisfied check nodes). Further, a trapping set maybe caused by the passing of incorrect information between the checknodes and variable nodes. To break the trapping set, any of a number ofdifferent techniques may be performed. For example, additional globaliterations of turbo equalizer 122, additional local iterations oferror-correction decoder 130, or a combination of additional global andlocal iterations may be performed. A global iteration is an iteration ofturbo equalizer 122 that includes channel detection,interleaving/de-interleaving, and error-correction decoding.

To perform an additional global iteration, error-correction decoder 130generates an extrinsic soft-output value Ext_(n) for each bit n of theerror-correction-encoded codeword as shown in Equation (1) below:Ext _(n) =P _(n) −L _(n) ⁽⁰⁾.   (1)The extrinsic soft-output values Ext_(n) are de-interleaved usingde-interleaver 128 and provided to channel detector 124. Channeldetector 124 performs another iteration of detection on the samplesy_(n) of the equalized, retrieved data stream, which are stored by turboequalizer 122 (not shown) during the first global iteration. In sodoing, channel detector 124 uses the extrinsic soft-output valuesExt_(n) to improve detection. For example, in Viterbi detection, theextrinsic soft-output values Ext_(n) are used to improve thebranch-metric calculation. Additionally, channel detector 124 uses theextrinsic soft-output values Ext_(n) to calculate new channelsoft-output values L_(n) as shown in Equation (2) as follows:L _(n) =Pdet _(n) −Ext _(n),   (2)where Pdet_(n) is an updated soft-output value generated by channeldetector 124 for each bit n of the error-correction-encoded codeword.The newly calculated channel soft-output values L_(n) are interleavedusing interleaver 126, and the interleaved channel soft-output valuesL_(n) are decoded using error-correction decoder 130.

Often, performing additional local and/or global iterations alone is notsufficient to break a trapping set. Thus, to break a trapping set,additional techniques may be needed. The following description discussesseveral techniques for breaking trapping sets that involve adjusting(e.g., noise biasing) different values within a turbo equalizer.Adjusting such values may steer error-correction decoder 130 away from atrapping set such that error-correction decoder 130 can recover thecorrect error-correction codeword.

Adjusting Soft-output Values in Turbo Equalization to Break TrappingSets

FIG. 2 shows a simplified block diagram of a turbo equalizer 200according to one embodiment of the present invention. Turbo equalizer200, which may be used, for example, in HDD systems such as HDD system100 of FIG. 1, is capable of processing one or more LDPC-encodedcodewords at a time. The number of LDPC-encoded codewords processed, andthe number of global and/or local iterations that may be performed foreach LDPC-encoded codeword may vary based on, for example, the memoryresources (e.g., y-memory 204, Q-memory 216) available at the time thatthe codeword is processed. As discussed below, turbo equalizer 200 iscapable of adjusting (i) the extrinsic soft-output values Ext_(n) outputfrom LDPC decoder 214 only, (ii) the channel soft-output values L_(n)output from channel detector 218 only, or (iii) both the extrinsicsoft-output values Ext_(n) and the channel soft-output values L_(n) tobreak trapping sets.

Turbo equalizer 200 receives equalized samples y_(n) of an outgoing datastream that are (i) retrieved from an HDD platter such as HDD platter106 of FIG. 1 and (ii) processed using, for example, a post-processorsuch as post-processor 120. During an initial global iteration, theequalized samples y_(n) are (i) stored in y-memory 204 for potential usein subsequent global iterations and (ii) processed by channel detector202, which performs detection analogous to channel detector 124 of FIG.1 to generate an initial channel soft-output value L_(n) ⁽⁰⁾ for eachbit n of the LDPC-encoded codeword. The initial channel soft-outputvalues L_(n) ⁽⁰⁾ are interleaved using interleaver 208 and stored byping-pong buffer 206. One of the buffers of ping-pong buffer 206 storesa set of channel soft-output values L_(n) ⁽⁰⁾ corresponding to thecurrent LDPC-encoded codeword that is currently being interleaved, whilethe other buffer outputs an interleaved set of channel soft-outputvalues L_(n) ⁽⁰⁾ corresponding to a previous LDPC-encoded codeword tothe upper input of multiplexer 212. Multiplexer 212, which may alsoreceive adjusted channel soft-output values L′_(n), as described below,selects the upper input of initial channel soft-output values L_(n) ⁽⁰⁾to output to LDPC decoder 214. Typically, the upper input of multiplexer212 is selected only during the first global iteration for anLDPC-encoded codeword, and the upper input of multiplexer 212 isselected for the subsequent global iterations.

LDPC decoder 214 performs one or more local iterations to recover theoriginal LDPC-encoded codeword as described above in relation toerror-correction decoder 130 of FIG. 1. If LDPC decoder 214 converges ona valid codeword, then LDPC decoder 214 provides hard-decision bitsx_(n) to buffer 220. Once a full set of hard-decision bits x_(n) isstored in buffer 220, the hard-decision bits x_(n) are de-interleavedusing de-interleaver 222 and output to, for example, a controller suchas controller 102 of FIG. 1. If LDPC decoder 214 converges on a trappingset, rather than a valid codeword, then turbo equalizer 200 may performa subsequent global iteration to break the trapping set. In so doing,extrinsic soft-output values Ext_(n) are output from LDPC decoder 214and stored in buffer 224. Some or all of the stored extrinsicsoft-output values Ext_(n) may be adjusted using adjustment block 226 asdescribed in further detail below in relation to FIG. 3. Thepossibly-adjusted extrinsic soft-output values Ext′_(n) are stored inQ-memory 216, which is implemented such that the possibly-adjustedextrinsic soft-output values Ext′_(n) are de-interleaved as they arestored in Q-memory 216.

Q-memory 216 provides the de-interleaved and possibly-adjusted extrinsicsoft-output values Ext′_(n) to channel detector 218. Channel detector218, which also receives the equalized samples y_(n) from y-memory 204performs detection analogous to channel detector 124 of FIG. 1 togenerate a subsequent channel soft-output value L_(n) for each bit n ofthe LDPC-encoded codeword. In so doing, channel detector 218 uses theextrinsic soft-output values Ext′_(n) to (i) improve detection asdescribed above and (ii) calculate new channel soft-output values L_(n)as shown in Equation (2) above.

Some or all of the new channel soft-output values L_(n) may be adjustedusing adjustment block 228 as described in further detail below inrelation to FIG. 3. The possibly-adjusted channel soft-output valuesL′_(n) are stored in Q-memory 216, which is implemented such that thepossibly-adjusted channel soft-output values L′_(n) are interleaved asthey are stored in Q-memory 216. The interleaved and possibly-adjustedchannel soft-output values L′_(n) are then stored in buffer 210,provided to the lower input of multiplexer 212, and output to LDPCdecoder 214. If LDPC decoder 214 does not successfully decode theinterleaved and possibly-adjusted channel soft-output values L′_(n),then subsequent global iterations of turbo equalizer 200 and/or localiterations of LDPC decoder 214 may be performed.

FIG. 3 shows a simplified flow diagram 300 of processing performed by aturbo equalizer such as turbo equalizer 200 of FIG. 2 according to oneembodiment of the present invention. For simplicity, some steps such asinterleaving, de-interleaving, storage in Q-memory, and storage in thevarious buffers are omitted. Upon startup, the equalized samples y_(n)are received (step 302) by the turbo equalizer. The equalized samplesy_(n) are stored for potential use in further global iterations (step304) of the turbo equalizer. Further, detection 306 is performed on theequalized samples y_(n) to generate an initial set of channelsoft-output values L_(n) ⁽⁰⁾ in a manner analogous to that describedabove in relation to channel detector 124 of FIG. 1.

The initial set of channel soft-output values L_(n) ⁽⁰⁾ are decoded 308in a manner analogous to that described above in relation toerror-correction decoder 130 of FIG. 1. A controller, such as controller102, performs decision 310 to determine whether the decoder hasconverged on a valid codeword by, for example, performing a syndromecheck. If the decoder has converged on a valid codeword, then thehard-decision bits x_(n) are output (step 312) to the controller andturbo equalization is stopped. If the decoder has not converged on avalid codeword, then the controller determines whether a trapping sethas been encountered (decision 314).

Determining whether the decoder has encountered a trapping may beperformed using any suitable method. For example, the controller maycompare the number of unsatisfied check nodes after a specified numberof iterations of the decoder to a specified threshold value (e.g., 16).If the number of unsatisfied check nodes is greater than or equal to thespecified threshold value, then it is likely that the decoder hasexperienced an error in the communication channel. If the number ofunsatisfied check nodes is less than the specified threshold value, thenit is likely that the decoder has converged on a trapping set. Asanother example, the decoder could track the number of unsatisfied checknodes over several iterations. If, over several iterations, the numberof unsatisfied check nodes is relatively stable, then this could beindicative of a trapping set. This method may be implemented by trackingthe variance of the number of unsatisfied check nodes over severaliterations. If the variance is less than a specified threshold value,then the LDPC decoder may suppose that a trapping set has beenencountered. This later example may be advantageous when the decoderconverges on a trapping set before the specified number of iterations.By identifying a trapping set before the specified number of iterations,the decoder can avoid performing unnecessary iterations.

As yet another example, the decoder could determine whether (i) thevector resulting from {circumflex over (x)}H^(T) possesses a number(b_(observed)) of unsatisfied check nodes that is greater than zero andless than a pre-defined threshold b_(max) (e.g., 16) and (ii) theparticular configuration of unsatisfied check nodes has remainedrelatively stable (i.e., the number and locations of the unsatisfiedcheck nodes have not changed) for several local iterations of the LDPCdecoder (e.g., two or three iterations). As yet still another example,the decoder could determine whether (i) the vector resulting from{circumflex over (x)}H^(T) possesses a number (b_(observed)) ofunsatisfied check nodes greater than zero and less than a pre-definedthreshold b_(max) (e.g., 16), and (ii) the particular configuration ofunsatisfied check nodes has remained relatively stable (i.e., unchanged)for several global iterations (e.g., two global iterations).

If the controller determines in decision 314 that the decoder has notconverged on a trapping set, then the decoder may determine (decision316) whether or not to perform additional local (i.e., decoder)iterations. For example, if the number of unsatisfied check nodes isrelatively large (e.g., greater than 16), then, as described above, thedecoder might have experienced an error in the communication channel. Insuch a case, it might not be possible for the decoder to recover thecorrect codeword, and the controller might initiate further actions(step 318) such as request a retransmission of the data. As anotherexample, the controller may determine whether the decoder has performedthe specified number of iterations. If the decoder has performed thespecified number of iterations, then additional global iterations may beperformed. If, on the other hand, the decoder has not performed thespecified number of iterations, then the controller may determine indecision 316 to continue decoding (i.e., perform an additional localiteration) and processing returns to step 308.

If the controller determines in decision 314 that the decoder hasconverged on a trapping set, then the controller determines in decision320 whether or not to perform an additional global iteration. Thisdetermination may be made, for example, based on whether or not aspecified number of global iterations have been performed. If thecontroller determines not to perform an additional global iteration,then further actions 318 may be needed to break the trapping set, suchas request a retransmission of the data. If the controller determines toperform an additional global iteration, then extrinsic soft-outputvalues Ext_(n) are output by the decoder (step 322).

To increase the likelihood of breaking the trapping set, the extrinsicsoft-output values Ext_(n) may be adjusted (step 326) by applying anadjustment value to some or all of the extrinsic soft-output valuesExt_(n). Adjustment may be performed, for example, by an adjustmentblock such as adjustment block 226 of FIG. 2. Further, adjustment may beperformed by, for example, applying an adjustment value such as (i) ascaling factor α (e.g., −1, −0.75, . . . , +0.75, +1) to the extrinsicsoft-output values Ext_(n) as shown in Equation (3) or (ii) an offsetvalue β to the extrinsic soft-output values Ext_(n) as shown in Equation(4) below:Ext′ _(n) =αExt _(n)  (3)Ext′ _(n)=sign(Ext _(n))×(|Ext _(n)|+β),   (4)where Ext′_(n) is the adjusted extrinsic soft-output value andsign(Ext_(n)) is the sign of the extrinsic soft-output value Ext_(n).Adjustment may also be performed by applying both a scaling factor andan offset value to the extrinsic soft-output values Ext_(n). Whenadjustment is first applied to the extrinsic soft-output values Ext_(n),preferably during the first iteration after reaching a trapping set, aninitial scaling factor and/or offset value is selected (step 324). Inthe case of scaling, the scaling factor α may be chosen such that themultiplication may be approximated using binary right and/or left shiftoperations. For example, shifting a binary value of 0110 (i.e., +6 indecimal format) one position to the right results in 0011 (i.e., +3 indecimal format), which is the equivalent of multiplying by a scalingfactor of 0.5. If the decoder does not converge on a correct codewordafter applying the initial scaling factor and/or offset value, thendifferent scaling factors and/or offset values may be selected duringsubsequent global iterations.

As another example, some or all of the extrinsic soft-output valuesExt_(n) may be saturated to decrease the confidence values of theextrinsic soft-output values Ext_(n). For example, suppose that theextrinsic soft-output values Ext_(n) range from −15, . . . , +15 insign-magnitude format. The extrinsic soft-output values Ext_(n) could besaturated to saturation levels other than −15, . . . , +15. For example,they could be saturated to −2, . . . , +2, such that an extrinsicsoft-output value Ext_(n) greater than +2 is mapped to +2, and anextrinsic soft-output value Ext_(n) less than −2 is mapped to −2. If thedecoder does not converge on a correct codeword after applying theinitial saturation levels, then different saturation levels may beselected during subsequent global iterations. An analogous saturationoperation may be performed for extrinsic soft-output values Ext_(n) thatare represented in two's complement format. As yet another alternative,some or all of the extrinsic soft-output values Ext_(n) could beadjusted using a combination of two or more of the scaling, offsetting,and saturation techniques.

Adjusting of the extrinsic soft-output values Ext_(n) may be eitherunconditional or conditional. Unconditional adjusting may be performedby adjusting the extrinsic soft-output values Ext_(n) without anyindependent determination as to which extrinsic soft-output valueExt_(n) should or should not be adjusted. For example, according someunconditional adjusting methods, every extrinsic soft-output valueExt_(n) may be scaled, offset, and/or saturated. According to otherunconditional adjusting methods, adjusting may be performed by addingrandom noise to the extrinsic soft-output values Ext_(n). Random noisemay be generated using any suitable method. For example, random noisemay be generated using a random noise generator. As another example,random noise may be generated by taking the difference of (i) the input,which comprises data and noise, of an FIR filter such as an FIR filterin a post-processor 120 of FIG. 1 and (ii) the FIR output, which iffiltered adequately comprises substantially only data. As one ofordinary skill in the art would recognize, random noise may have a valueof zero in some locations. Thus, when random noise is added to all ofthe extrinsic soft-output values Ext_(n), it is possible that some ofthe extrinsic soft-output values Ext_(n) will not be changed.

Conditional adjusting may be performed to independently select some, butnot all, of the extrinsic soft-output values Ext_(n) for scaling,offsetting, and/or saturating. For example, according to a firstconditional adjusting method, the controller identifies the locations ofthe unsatisfied check nodes of the last local decoder iteration. Thismay be performed by identifying the locations of the elements in thesyndrome that have a value of one. Then, the extrinsic soft-outputvalues Ext_(n) corresponding to bit nodes (i.e., columns of the LDPCparity-check matrix) of the LDPC-encoded codeword that are connected tothe identified unsatisfied check nodes may be adjusted.

According to other conditional adjusting methods, the controllerdetermines whether or not to adjust each extrinsic soft-output valueExt_(n) based on a comparison of the signs of two correspondingsoft-output values as illustrated in Table I below. If the sign bitsdisagree, then the corresponding extrinsic soft-output value Ext_(n) isadjusted. If the sign bits agree, then the corresponding extrinsicsoft-output values Ext_(n) is not adjusted. Table I shows some of thesoft-output values that could be compared.

TABLE I First Soft-Output Value Second Soft-Output Value 1sign(Pdet_(n)) sign(P_(n)) 2 sign(Pdet_(n)) sign(L_(n)) 3 sign(Pdet_(n))sign(Ext_(n)) 4 sign(L_(n)) sign(Ext_(n)) 5 sign(L_(n)) sign(P_(n)) 6sign(Ext_(n)) sign(P_(n))

As shown in the first row, the sign of the updated soft-output valuePdet_(n) generated by the channel detector corresponding to the n^(th)bit of the error-correction-encoded codeword could be compared to theupdated soft-output value P_(n) generated by the error-correctiondecoder corresponding to the n^(th) bit. As shown in the second row, thesign of the updated soft-output value Pdet_(n) generated by the channeldetector corresponding to the n^(th) bit could be compared to theupdated channel soft-output value L_(n) generated by the channeldetector corresponding to the n^(th) bit. As shown in the third row, thesign of the updated soft-output value Pdet_(n) generated by the channeldetector corresponding to the n^(th) bit could be compared to theupdated extrinsic soft-output value Ext_(n) generated by theerror-correction decoder corresponding to the n^(th) bit. As shown inthe fourth row, the sign of the updated channel soft-output value L_(n)generated by the channel detector corresponding to the n^(th) bit couldbe compared to the updated extrinsic soft-output value Ext_(n) generatedby the error-correction decoder corresponding to the n^(th) bit. Asshown in the fifth row, the sign of the updated channel soft-outputvalue L_(n) generated by the channel detector corresponding to then^(th) bit could be compared to the updated soft-output value P_(n)generated by the error-correction decoder corresponding to the n^(th)bit. As shown in the sixth row, the updated extrinsic soft-output valueExt_(n) generated by the error-correction decoder corresponding to then^(th) bit could be compared to the updated soft-output value P_(n)generated by the error-correction decoder corresponding to the n^(th)bit.

After the extrinsic soft-output values Ext_(n) are output and possiblyadjusted, channel detection (step 328) is performed on the equalizedsamples y_(n) stored in step 304 to generate subsequent channelsoft-output values L_(n). In so doing, the possibly-adjusted extrinsicsoft-output values Ext′_(n) are used to improve the channel detectioncapabilities as described above. To increase the likelihood of breakingthe trapping set, some or all of the subsequent channel soft-outputvalues L_(n) output by the channel detector may be adjusted (e.g., noisebiased) (step 332) by applying an adjustment value to some or all of thesubsequent channel soft-output values L_(n). Adjustment may beperformed, for example, by an adjustment block such as adjustment block228 of FIG. 2. Further, adjustment may be performed, for example, byapplying an adjustment value such as (i) a scaling factor α (e.g., −1,−0.75, . . . , +0.75, +1) to the subsequent channel soft-output valuesL_(n) as shown in Equation (5) or (ii) an offset value β to thesubsequent channel soft-output values L_(n) as shown in Equation (6)below:L′ _(n) =αL _(n)   (5)L′ _(n)=sign(L _(n))×(|L _(n)|+β),   (6)where L′_(n) is the subsequent channel soft-output value L_(n) andsign(L_(n)) is the sign of the subsequent channel soft-output valueL_(n). Adjustment may also be performed by applying both a scalingfactor and an offset value to the channel soft-output value L_(n). Whenadjustment is first applied to the subsequent channel soft-output valuesL_(n), preferably during the first iteration after reaching a trappingset, an initial scaling factor and/or offset value is selected (step330). If the decoder does not converge on a correct codeword afterapplying the initial scaling factor and/or offset value, then differentscaling factors and/or offset values may be selected during subsequentglobal iterations.

As another example, some or all of the channel soft-output values L_(n)may be saturated in a manner similar to that described above in relationto the extrinsic soft-output values Ext_(n) to decrease the confidencevalues of the channel soft-output values L_(n). As yet anotheralternative, some or all of the extrinsic soft-output values Ext_(n)could be adjusted using a combination of two or more of the scaling,offsetting, and saturation techniques.

Adjustment of the subsequent channel soft-output values L_(n) may beperformed conditionally or unconditionally in a manner similar to thatdescribed above in relation to step 326. For example, the subsequentchannel soft-output values L_(n) may be unconditionally adjusted byapplying a scaling factor, offset value, and/or saturation to all of thesubsequent channel soft-output values L_(n) or random noise may be addedto the subsequent channel soft-output values L_(n). As another example,each subsequent channel soft-output value L_(n) may be conditionallyadjusted based on, for example, (i) the locations of the unsatisfiedcheck nodes of the last local decoder iteration or (ii) a comparison ofthe signs of two corresponding soft-output values as illustrated inTable I.

The possibly-adjusted subsequent channel soft-output values L′_(n) arethen decoded (step 308). If the controller determines that the decoderconverged on a trapping set again (step 314), then a subsequent globaliteration may be performed where the controller selects new adjustmentvalues (steps 324 and/or 330) for adjusting the extrinsic soft-outputvalues Ext_(n) and/or the subsequent channel soft-output values L_(n)(steps 326 and/or 332). If the controller determines that the decoderhas not converged on a trapping set, then step 316 is performed asdescribed above.

Adjusting Equalized Samples in Turbo Equalization to Break Trapping Sets

FIG. 4 shows a simplified block diagram of a turbo equalizer 400according to another embodiment of the present invention. Similar toturbo equalizer 200 of FIG. 2, turbo equalizer 400 may be used, forexample, in an HDD system such as HDD system 100 of FIG. 1, and iscapable of processing one or more error-correction-encoded codewords ata time. The number of error-correction-encoded codewords processed, andthe number of global and/or local iterations that may be performed foreach error-correction-encoded codeword may vary based on, for example,the memory resources (e.g., y-memory 404, Q-memory 416) available at thetime that the codeword is processed. Further, as described below, turboequalizer 400 is capable of adjusting (e.g., biasing) equalized,retrieved samples y_(n) to break trapping sets.

Turbo equalizer 400 receives equalized samples y_(n) of an outgoing datastream that are (i) retrieved from an HDD platter such as HDD platter106 of FIG. 1 and (ii) processed using, for example, a post-processorsuch as post-processor 120. During the initial global iteration, theequalized samples y_(n) are provided to (i) the upper input ofmultiplexer 430 and (ii) channel detector 402. Multiplexer 430, whichmay also receive adjusted samples y′_(n) via its lower input, providesits upper input to y-memory 404, which stores the equalized samplesy_(n) for potential use in subsequent global iterations.

Channel detector 402, ping-pong buffer 406, interleaver 408, multiplexer412, and LDPC decoder 414 perform operations analogous to the equivalentprocessing of turbo decoder 200 of FIG. 2. If LDPC decoder 414 convergeson a valid codeword, then LDPC decoder 414 provides hard-decision bitsx_(n) to buffer 420 and de-interleaver 422, which perform operationsanalogous to buffer 220 and de-interleaver 222 of FIG. 2. If LDPCdecoder 414 converges on a trapping set, rather than a valid codeword,then turbo equalizer 400 may perform a subsequent global iteration usingy-sample adjustments (e.g., noise biasing) to break the trapping set. Inso doing, extrinsic soft-values Ext_(n) are output from LDPC decoder 414and stored in buffer 424. After storing the extrinsic soft-output valuesExt_(n), saturation block 426 may saturate the extrinsic soft-outputvalues Ext_(n) such that they are maintained within a specified range.Saturation may be performed in a manner analogous to that describedabove in relation to step 326 of FIG. 3. The possibly-saturatedextrinsic soft-output values Ext_(n) are then stored in Q-memory 416,which performs operations analogous to Q-memory 216 of FIG. 2 (i.e.,storing, interleaving, de-interleaving). Note that, according toalternative embodiments of the present invention, scaling and/oroffsetting may be used in addition to, or in lieu of, saturation block426.

Q-memory 416 provides de-interleaved and possibly-saturated extrinsicsoft-values Ext_(n) to channel detector 418. Channel detector 418performs operations analogous to channel detector 218 of FIG. 2 togenerate subsequent channel soft-output values L_(n); however, ratherthan performing channel detection on the equalized, retrieved samplesy_(n), channel detector 418 performs detection on adjusted samplesy′_(n). In particular, the equalized, retrieved samples y_(n) stored iny-memory 404 are provided to delay buffer 434. Some or all of theequalized, retrieved samples y_(n) are adjusted using adjustment block432, which performs conditional adjusting (e.g., noise biasing) asdescribed in further detail below in relation to FIG. 5. Thepossibly-adjusted samples y′_(n) are provided to the lower input ofmultiplexer 430 and are subsequently stored in y-memory 404 before beingprocessed by channel detector 418.

After channel detection, the subsequent channel soft-output values L_(n)may be saturated using saturation block 428, which operates in a manneranalogous to saturation block 426, and the possibly-saturated subsequentchannel soft-output values L_(n) are interleaved and stored in Q-memory416. Note that, according to alternative embodiments of the presentinvention, scaling and/or offsetting may be used in addition to, or inlieu of, saturation block 428. The interleaved channel soft-outputvalues L_(n) are then stored in buffer 410, provided to the lower inputof multiplexer 412, and output to LDPC decoder 414. If LDPC decoder 414does not successfully decode the interleaved channel soft-output valuesL_(n), then subsequent global iterations of turbo equalizer 400 and/orlocal iterations of LDPC decoder 414 may be performed.

FIG. 5 shows a simplified flow diagram 500 of processing performed by aturbo equalizer such as turbo equalizer 400 of FIG. 4 according to oneembodiment of the present invention. For simplicity, some steps such asinterleaving, de-interleaving, storage in Q-memory, and storage invarious buffers have been omitted. Upon startup, the equalized,retrieved input data samples y_(n) are received (e.g., step 502) by theturbo equalizer. The equalized, retrieved input data samples y_(n) arestored (step 504) for potential use in further global iterations of theturbo equalizer. During the first global iteration, steps 506-518 areperformed in a manner analogous to that of the equivalent steps of flowdiagram 300 of FIG. 3. If, during the first global iteration, thedecoder converges on a trapping set (decision 514), and, if thecontroller determines to perform another global iteration (decision520), then one or more combinations of subsequent global iterations ofthe turbo equalizer and/or local iterations of the error-correctiondecoder may be performed.

In performing a subsequent global iteration, extrinsic soft-outputvalues Ext_(n) are output from the error-correction decoder. Theextrinsic soft-output values Ext_(n) are possibly saturated (step 524)in a manner analogous to that described above in relation to step 324 ofFIG. 3, and the possibly-saturated extrinsic soft-output values Ext_(n)are provided to the channel detector for use in improving the detectioncapabilities of the channel detector as described above.

Before performing channel detection (step 530), the equalized samplesy_(n) stored in step 504 are conditionally adjusted (step 526) toincrease the likelihood of breaking the trapping set. Conditionaladjusting of equalized samples y_(n) may be performed in a mannersimilar to that described above in relation to step 324 of FIG. 3. Forexample, one or more of the equalized samples y_(n) may be selectedbased on, for example, (i) the locations of the unsatisfied check nodesof the last local decoder iteration or (ii) a comparison of the signs oftwo corresponding soft-output values as illustrated in Table I. Theselected equalized samples y_(n) may then be adjusted by, for example,an adjustment block such as adjustment block 432 of FIG. 4. Adjustmentmay be performed by applying a scaling factor as shown in Equation (7)or an offset value as shown in Equation (8) below:y′ _(n) =αy _(n)   (7)y′ _(n)=sign(y _(n))×(|y _(n)|+β),   (8)where y′_(n) is the adjusted equalized sample and sign(y_(n)) is thesign of the equalized samples y_(n). Adjustment may also be performed byapplying both a scaling factor and an offset value to the equalizedsamples y_(n). Alternatively, or in addition, the equalized samplesy_(n) may be saturated in a manner similar to that described in relationto step 324 of FIG. 3.

After channel detection (step 530), subsequent channel soft-outputvalues L_(n) are output from the channel detector and possibly saturated(step 532) in a manner similar to that described above in relation tostep 324 of FIG. 3. The possibly-saturated subsequent channelsoft-output values L_(n) are then decoded (step 508). If the controllerdetermines that the decoder converged on a trapping set again (step514), then a subsequent global iteration may be performed where thecontroller selects a new scaling factor and/or offset value (step 526)for adjusting the equalized samples y_(n) in step 528. If the controllerdetermines that the decoder has not converged on a trapping set, thenstep 516 is performed.

Conclusion

Although the present invention was described relative to its use in HDDsystems, the present invention is not so limited. The present inventionmay be used in other storage systems, or in applications other thanstorage devices such as communication receivers.

The present invention may be used in turbo equalizers other than theexemplary turbo equalizers provided in this application. One of ordinaryskill in the art would recognize that there are many differentconfigurations of turbo equalizers, and that the present invention maybe applied to turbo equalizers having configurations different fromthose provided in this application. Such other turbo equalizers mayemploy channel detection other than Viterbi detection and/or othererror-correction decoding other than LDPC decoding. Such other turboequalizers may employ one channel detector or more than one channeldetector. Also, such other turbo equalizers may employ oneerror-correction decoder as shown in FIG. 2 or more than oneerror-correction decoder.

Further, the present invention is not limited to adjusting extrinsicsoft-output values Ext_(n), channel soft-output values L_(n), andequalized samples y_(n). For example, the various embodiments of thepresent invention may adjust (i) updated soft-output values P_(n)generated by the error-correction decoder in addition to, or in lieu of,the extrinsic soft-output values and/or (ii) updated soft-output valuesPdet_(n) generated by the channel detector in addition to, or in lieuof, the channel soft-output values L_(n).

It will be further understood that various changes in the details,materials, and arrangements of the parts which have been described andillustrated in order to explain the nature of this invention may be madeby those skilled in the art without departing from the scope of theinvention as expressed in the following claims. For example, in FIG. 2,rather than adjusting extrinsic soft-output values Ext_(n) beforestorage in Q-memory 216, the extrinsic soft-output values Ext_(n) may beadjusted after storage in Q-memory 216. Similarly, channel soft-outputvalues L_(n) may be adjusted after storage in Q-memory 216.

Further embodiments of the present invention may be envisioned whichemploy a combination of two or more of y-sample adjusting, extrinsicsoft-output value Ext_(n) adjusting, and channel soft-output L_(n)adjusting to break trapping sets.

While the exemplary embodiments of the present invention have beendescribed with respect to processes of circuits, including possibleimplementation as a single integrated circuit, a multi-chip module, asingle card, or a multi-card circuit pack, the present invention is notso limited. As would be apparent to one skilled in the art, variousfunctions of circuit elements may also be implemented as processingblocks in a software program. Such software may be employed in, forexample, a digital signal processor, micro-controller, or generalpurpose computer.

The present invention can be embodied in the form of methods andapparatuses for practicing those methods. The present invention can alsobe embodied in the form of program code embodied in tangible media, suchas magnetic recording media, optical recording media, solid statememory, floppy diskettes, CD-ROMs, hard drives, or any othermachine-readable storage medium, wherein, when the program code isloaded into and executed by a machine, such as a computer, the machinebecomes an apparatus for practicing the invention. The present inventioncan also be embodied in the form of program code, for example, whetherstored in a storage medium, loaded into and/or executed by a machine, ortransmitted over some transmission medium or carrier, such as overelectrical wiring or cabling, through fiber optics, or viaelectromagnetic radiation, wherein, when the program code is loaded intoand executed by a machine, such as a computer, the machine becomes anapparatus for practicing the invention. When implemented on ageneral-purpose processor, the program code segments combine with theprocessor to provide a unique device that operates analogously tospecific logic circuits. The present invention can also be embodied inthe form of a bitstream or other sequence of signal values electricallyor optically transmitted through a medium, stored magnetic-fieldvariations in a magnetic recording medium, etc., generated using amethod and/or an apparatus of the present invention.

Unless explicitly stated otherwise, each numerical value and rangeshould be interpreted as being approximate as if the word “about” or“approximately” preceded the value of the value or range.

The use of figure numbers and/or figure reference labels in the claimsis intended to identify one or more possible embodiments of the claimedsubject matter in order to facilitate the interpretation of the claims.Such use is not to be construed as necessarily limiting the scope ofthose claims to the embodiments shown in the corresponding figures.

It should be understood that the steps of the exemplary methods setforth herein are not necessarily required to be performed in the orderdescribed, and the order of the steps of such methods should beunderstood to be merely exemplary. Likewise, additional steps may beincluded in such methods, and certain steps may be omitted or combined,in methods consistent with various embodiments of the present invention.

Although the elements in the following method claims, if any, arerecited in a particular sequence with corresponding labeling, unless theclaim recitations otherwise imply a particular sequence for implementingsome or all of those elements, those elements are not necessarilyintended to be limited to being implemented in that particular sequence.

We claim:
 1. An apparatus for recovering an error-correction encodedcodeword from a set of input samples, the apparatus comprising: at leastone channel detector adapted to perform channel detection on the set ofinput samples to generate a first set of soft-input values; anerror-correction decoder adapted to (i) perform error-correctiondecoding on the first set of soft-input values to attempt to recover theerror-correction-encoded codeword and (ii) generate a first set ofsoft-output values, each soft-output value corresponding to a bit of theerror-correction-encoded codeword; and an adjuster adapted to adjust, ifthe error-correction decoder converges on a trapping set, one or more ofthe input samples to generate an adjusted set of input samples, whereinthe apparatus is adapted to determine whether one or more specifiedconditions exist to select the one or more input samples for adjustment,wherein: the at least one channel detector is further adapted to performchannel detection to generate a second set of soft-output values forsubsequent error-correction decoding, wherein: the second set ofsoft-output values is generated based on (i) the adjusted set of inputsamples and (ii) the first set of soft-output values; and eachsoft-output value in the second set corresponds to a bit of theerror-correction-encoded codeword.
 2. The apparatus of claim 1, wherein,if the error-correction decoder converges on a trapping set, then theapparatus: identifies (i) locations of unsatisfied check nodes in theerror-correction decoder and (ii) locations of bit nodes that areconnected to the unsatisfied check nodes; and selects the one or moreinput samples for adjustment such that each selected input samplecorresponds to an identified bit node location.
 3. The apparatus ofclaim 1, wherein, for each input sample, the apparatus: compares (i) asign bit of a first comparison value that corresponds to the inputsample and (ii) a sign bit of a second comparison value that correspondsto the input sample; and selects the input sample for adjustment if thecomparison indicates that the sign bits of the first and the secondcomparison values disagree.
 4. The apparatus of claim 3, wherein: thefirst comparison value is one of an extrinsic soft-output value, anupdated soft-output value generated by the at least one channeldetector, and a channel soft-output value corresponding to thesoft-output value; and the second comparison value is one of an updatedsoft-output value generated by the error-correction decoder, a channelsoft-output value, and an extrinsic soft-output value corresponding tothe soft-output value, wherein the first comparison value is differentfrom the second comparison value.
 5. The apparatus of claim 4, wherein:the first comparison value is an extrinsic soft-output valuecorresponding to the soft-output value; and the second comparison valueis a channel soft-output value corresponding to the soft-output value.6. The apparatus of claim 1, wherein the adjuster adjusts the one ormore input samples by applying a scaling factor to the one or more inputsamples.
 7. The apparatus of claim 1, wherein the adjuster adjusts theone or more input samples by applying an offset value to the one or moreinput samples.
 8. The apparatus of claim 1, wherein the adjuster adjuststhe one or more input samples by applying one or more saturation levelsto the one or more input samples.
 9. The apparatus of claim 1, whereinthe apparatus selects fewer than all of the input samples foradjustment.
 10. The apparatus of claim 1, wherein: the adjuster adjuststhe one or more input samples by applying one or more of (i) a scalingfactor, (ii) an offset value, and (iii) one or more saturation levels tothe one or more input samples; and the apparatus dynamically adjusts oneor more of (i) the scaling factor, (ii) the offset value, and (iii) theone or more saturation levels.
 11. The apparatus of claim 1, wherein theerror-correction decoder is a low-density parity-check decoder.
 12. Theapparatus of claim 1, wherein the apparatus comprises one or more otheradjusters adapted to adjust at least one set of (i) the first set ofsoft-output values before the channel detection and (ii) the second setof soft-output values before the subsequent error-correction decoding.13. The apparatus of claim 12, wherein the one or more other adjustersadjust the at least one set by applying one or more saturation levels tothe at least one set.
 14. A method for recovering an error-correctionerror-correction-encoded codeword from a set of input samples, themethod comprising: (a) performing channel detection on the set of inputsamples to generate a first set of soft-input values; (b) performingerror-correction decoding on the first set of soft-input values toattempt to recover the error-correction-encoded codeword; (c) generatinga first set of soft-output values, each soft-output value correspondingto a bit of the error-correction-encoded codeword; (d) determining, ifthe error-correction decoding converges on a trapping set, whether oneor more specified conditions exist to select one or more of the inputsamples for adjustment, and adjusting the one or more input samples togenerate an adjusted set of input samples; and (e) performing channeldetection to generate a second set of soft-output values for subsequenterror-correction decoding, wherein: the second set of soft-output valuesis generated based on (i) the adjusted set of input samples and (ii) thefirst set of soft-output values; and each soft-output value in thesecond set corresponds to a bit of the error-correction-encodedcodeword.
 15. The method of claim 14, wherein, if the error-correctiondecoding converges on a trapping set, then step (c) comprises: (c1)identifying locations of unsatisfied check nodes encountered during theerror-correction decoding; (c2) identifying locations of bit nodes thatare connected to the unsatisfied check nodes; and (c3) selecting the oneor more input samples for adjustment such that each selected inputsample corresponds to an identified bit node location.
 16. The method ofclaim 14, wherein, for each input sample, step (c) comprises: (c1)comparing (i) a sign bit of a first comparison value that corresponds tothe input sample and (ii) a sign bit of a second comparison value thatcorresponds to the input sample; and (c2) selecting the input sample foradjustment if the comparison indicates that the sign bits of the firstand the second comparison values disagree.
 17. The method of claim 16,wherein: the first comparison value is one of an extrinsic soft-outputvalue, an updated soft-output value generated by the channel detector,and a channel soft-output value corresponding to the soft-output value;and the second comparison value is one of an updated soft-output valuegenerated by the error-correction decoder, a channel soft-output value,and an extrinsic soft-output value corresponding to the soft-outputvalue, wherein the first comparison value is different from the secondcomparison value.
 18. The method of claim 17, wherein: the firstcomparison value is an extrinsic soft-output value corresponding to thesoft-output value; and the second comparison value is a channelsoft-output value corresponding to the soft-output value.
 19. The methodof claim 14, step (c) comprises: (c1) adjusting the one or more inputsamples by applying one or more of (i) a scaling factor, (ii) an offsetvalue, and (iii) one or more saturation levels to the one or more inputsamples; and (c2) dynamically adjusting one or more of (i) the scalingfactor, (ii) the offset value, and (iii) the one or more saturationlevels.
 20. The method of claim 14, further comprising: (e) adjusting atleast one set of (i) the first set of soft-output values before thechannel detection and (ii) the second set of soft-output values beforethe subsequent error-correction decoding.
 21. An apparatus forrecovering an error-correction-encoded codeword from a set of inputsamples, the apparatus comprising: an error-correction decoder adaptedto (i) perform error-correction decoding to attempt to recover theerror-correction-encoded codeword and (ii) generate a first set ofsoft-output values, each soft-output value corresponding to a bit of theerror-correction-encoded codeword; an adjuster adapted to adjust, if theerror-correction decoder converges on a trapping set, one or more of theinput samples to generate an adjusted set of input samples, wherein theapparatus is adapted to determine whether one or more specifiedconditions exist to select the one or more input samples for adjustment;and a channel detector adapted to perform channel detection to generatea second set of soft-output values for subsequent error-correctiondecoding, wherein: the second set of soft-output values is generatedbased on (i) the adjusted set of input samples and (ii) the first set ofsoft-output values; and each soft-output value in the second setcorresponds to a bit of the error-correction-encoded codeword, wherein:for each input sample, the apparatus: compares (i) a sign bit of a firstcomparison value that corresponds to the input sample and (ii) a signbit of a second comparison value that corresponds to the input sample;and selects the input sample for adjustment if the comparison indicatesthat the sign bits of the first and the second comparison valuesdisagree, wherein: the first comparison value is one of an extrinsicsoft-output value, an updated soft-output value generated by the channeldetector, and a channel soft-output value corresponding to thesoft-output value; and the second comparison value is one of an updatedsoft-output value generated by the error-correction decoder, a channelsoft-output value, and an extrinsic soft-output value corresponding tothe soft-output value, wherein the first comparison value is differentfrom the second comparison value.
 22. The apparatus of claim 21,wherein: the first comparison value is an extrinsic soft-output valuecorresponding to the soft-output value; and the second comparison valueis a channel soft-output value corresponding to the soft-output value.23. A method for recovering an error-correction error-correction-encodedcodeword from a set of input samples, the method comprising: (a)performing error-correction decoding to attempt to recover theerror-correction-encoded codeword; (b) generating a first set ofsoft-output values, each soft-output value corresponding to a bit of theerror-correction-encoded codeword; (c) determining, if theerror-correction decoding converges on a trapping set, whether one ormore specified conditions exist to select one or more of the inputsamples for adjustment, and adjusting the one or more input samples togenerate an adjusted set of input samples; and (d) performing channeldetection to generate a second set of soft-output values for subsequenterror-correction decoding, wherein: the second set of soft-output valuesis generated based on (i) the adjusted set of input samples and (ii) thefirst set of soft-output values; and each soft-output value in thesecond set corresponds to a bit of the error-correction-encodedcodeword, wherein: for each input sample, step (c) comprises: (c1)comparing (i) a sign bit of a first comparison value that corresponds tothe input sample and (ii) a sign bit of a second comparison value thatcorresponds to the input sample; and (c2) selecting the input sample foradjustment if the comparison indicates that the sign bits of the firstand the second comparison values disagree, wherein: the first comparisonvalue is one of an extrinsic soft-output value, an updated soft-outputvalue generated by the channel detector, and a channel soft-output valuecorresponding to the soft-output value; and the second comparison valueis one of an updated soft-output value generated by the error-correctiondecoder, a channel soft-output value, and an extrinsic soft-output valuecorresponding to the soft-output value, wherein the first comparisonvalue is different from the second comparison value.
 24. The method ofclaim 23, wherein: the first comparison value is an extrinsicsoft-output value corresponding to the soft-output value; and the secondcomparison value is a channel soft-output value corresponding to thesoft-output value.